A research on grey numerical imitation and modeling of groundwater seepage system

来源 :Science in China(Series D:Earth Sciences) | 被引量 : 0次 | 上传用户:jiguoqiang
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Based on grey set, grey numbers and their operation properties, the grey numerical model of groundwater seepage system was set up for the first time, the whole grey solving method of the model was given and it was proved that the common solving method of the model was only a special case of the grey solving methods. At the same time, the grey solving method was compared widely with common solving method, classical numerical method. The study shows that the grey solving method is better in depicting the procedure of transporting grey data of ground-water system. On the basis of the theoretical study, two basic kinds of cases about groundwater seepage were selected: the prediction of pit yield and the evaluation of groundwater resources on a groundwater basin. In the cases, systematical analyses were made for generalization and grey-lization of the hydrogeologic conditions, setting up of the grey model, identification and correction of the model as well as its prediction and evaluation. It was pointed out Based on gray set, gray numbers and their operation properties, the gray numerical model of groundwater seepage system was set up for the first time, the whole gray solving method of the model was given and it was verified that the common solving method of the model was only a special case of the gray solving methods. At the same time, the gray solving method was compared widely with common solving method, classical numerical method. The study shows that the gray solving method is better in describing the procedure of transporting gray data On the basis of the theoretical study, two basic kinds of cases about groundwater seepage were selected: the prediction of pit yield and the evaluation of groundwater resources on a groundwater basin. In the cases, systematical analyzes were made for generalization and gray-lization of the hydrogeologic conditions, setting up of the gray model, identification and correction of the model as well as its prediction and evaluation. It was pointed out
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